Exploring the Prevalence and Components of Metabolic Syndrome in Sub-Saharan African Type 2 Diabetes Mellitus Patients: A Systematic Review and Meta-Analysis

Background Type 2 diabetes mellitus and metabolic syndrome represent two closely intertwined public health challenges that have reached alarming epidemic proportions in low- and middle-income countries, particularly in sub-Saharan Africa. Therefore, the current study aimed to determine the weighted pooled prevalence of metabolic syndrome and its components among individuals with type 2 diabetes mellitus in sub-Saharan Africa as defined by the 2004 National Cholesterol Education Program-Adult Treatment Panel (NCEP-ATP III 2004) and/or the International Diabetes Federation (IDF) criteria. Methods A systematic search was conducted to retrieve studies published in the English language on the prevalence of metabolic syndrome among type 2 diabetic individuals in sub-Saharan Africa. Searches were carried out in PubMed, Embase, Scopus, Google Scholar, African Index Medicus, and African Journal Online from their inception until July 31, 2023. A random-effects model was employed to estimate the weighted pooled prevalence of metabolic syndrome in sub-Saharan Africa. Evidence of between-study variance attributed to heterogeneity was assessed using Cochran's Q statistic and the I2 statistic. The Joanna Briggs Institute quality appraisal criteria were used to evaluate the methodological quality of the included studies. The summary estimates were presented with forest plots and tables. Publication bias was checked with the funnel plot and Egger's regression test. Results Overall, 1421 articles were identified and evaluated using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and 30 studies that met the inclusion criteria were included in the final analysis. The weighted pooled prevalence of metabolic syndrome among individuals with type 2 diabetes mellitus in sub-Saharan Africa was 63.1% (95% CI: 57.9–68.1) when using the NCEP-ATP III 2004 criteria and 60.8% (95% CI: 50.7–70.0) when using the IDF criteria. Subgroup analysis, using NCEP-ATP III 2004 and IDF criteria, revealed higher weighted pooled prevalence among females: 73.5% (95% CI: 67.4–79.5), 71.6% (95% CI: 60.2–82.9), compared to males: 50.5% (95% CI: 43.8–57.2), 44.5% (95% CI: 34.2–54.8), respectively. Central obesity was the most prevalent component of metabolic syndrome, with a pooled prevalence of 55.9% and 61.6% using NCEP-ATP III 2004 and IDF criteria, respectively. There was no statistical evidence of publication bias in both the NCEP-ATP III 2004 and IDF pooled estimates. Conclusions The findings underscore the alarming prevalence of metabolic syndrome among individuals with type 2 diabetes mellitus in sub-Saharan Africa. Therefore, it is essential to promote lifestyle modifications, such as regular exercise and balanced diets, prioritize routine obesity screenings, and implement early interventions and robust public health measures to mitigate the risks associated with central obesity.

Background.Type 2 diabetes mellitus and metabolic syndrome represent two closely intertwined public health challenges that have reached alarming epidemic proportions in low-and middle-income countries, particularly in sub-Saharan Africa.Terefore, the current study aimed to determine the weighted pooled prevalence of metabolic syndrome and its components among individuals with type 2 diabetes mellitus in sub-Saharan Africa as defned by the 2004 National Cholesterol Education Program-Adult Treatment Panel (NCEP-ATP III 2004) and/or the International Diabetes Federation (IDF) criteria.Methods.A systematic search was conducted to retrieve studies published in the English language on the prevalence of metabolic syndrome among type 2 diabetic individuals in sub-Saharan Africa.Searches were carried out in PubMed, Embase, Scopus, Google Scholar, African Index Medicus, and African Journal Online from their inception until July 31, 2023.A random-efects model was employed to estimate the weighted pooled prevalence of metabolic syndrome in sub-Saharan Africa.Evidence of between-study variance attributed to heterogeneity was assessed using Cochran's Q statistic and the I2 statistic.Te Joanna Briggs Institute quality appraisal criteria were used to evaluate the methodological quality of the included studies.Te summary estimates were presented with forest plots and tables.Publication bias was checked with the funnel plot and Egger's regression test.Results.Overall, 1421 articles were identifed and evaluated using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and 30 studies that met the inclusion criteria were included in the fnal analysis.Te weighted pooled prevalence of metabolic syndrome among individuals with type 2 diabetes mellitus in sub-Saharan Africa was 63.1% (95% CI: 57.9-68.1)when using the NCEP-ATP III 2004 criteria and 60.8% (95% CI: 50.7-70.0)when using the IDF criteria.Subgroup analysis, using NCEP-ATP III 2004 and IDF criteria, revealed higher weighted pooled prevalence among females: 73.5% (95% CI: 67.4-79.5),71.6% (95% CI: 60.2-82.9),compared to males: 50.5% (95% CI: 43.8-57.2),44.5% (95% CI: 34.2-54.8),respectively.Central obesity was the most prevalent component of metabolic syndrome, with a pooled prevalence of 55.9% and 61.6% using NCEP-ATP III 2004 and IDF criteria, respectively.Tere was no statistical evidence of publication bias in both the NCEP-ATP III 2004 and IDF pooled estimates.Conclusions.Te fndings underscore the alarming prevalence of metabolic syndrome among individuals with type 2 diabetes mellitus in sub-Saharan Africa.Terefore, it is essential to promote lifestyle modifcations, such as regular exercise and balanced diets, prioritize routine obesity screenings, and implement early interventions and robust public health measures to mitigate the risks associated with central obesity.

Introduction
Metabolic syndrome (MetS), characterized by a constellation of interconnected risk factors such as abdominal obesity, high blood pressure, high blood glucose, and abnormal lipid profles, poses a signifcant risk to individuals worldwide [1,2].When coexisting with type 2 diabetes mellitus (T2DM), this syndrome can exacerbate the progression of the disease and increase the risk of cardiovascular diseases [3,4], which are the leading cause of mortality worldwide [5,6].Sub-Saharan Africa (SSA), home to over one billion people, is not immune to these global health trends [7].Owing to the increase in urbanization, excessive alcohol consumption, unhealthy eating habits, smoking, sedentary lifestyles, and overweight [8,9], SSA, like many other regions, is currently witnessing a rapid epidemiological shift characterized by an increasing predominance of noncommunicable diseases (NCDs) [10], contributing to a growing prevalence of both T2DM and MetS in the region.
T2DM is the most common chronic metabolicendocrine disorder afecting adults.It results from a complex interaction between heredity along with other risk factors such as insulin resistance, obesity, physical inactivity, an unhealthy diet, smoking, and excessive alcohol consumption [11].Its multisystemic nature suggests that complications and comorbidities have the potential to impact various organ systems [12], particularly in the setting of poor blood glucose control.Te burden of T2DM in sub-Saharan Africa has grown into a substantial public health challenge.According to the International Diabetes Federation (IDF) report, the greatest relative increase in the prevalence of diabetes between 2021 and 2045 will occur in low-income countries (11.9%) and middle-income countries (21.1%), which largely includes SSA countries [13].
Globally, the prevalence of MetS is escalating at an alarming rate, and it is highly prevalent in patients with T2DM [14,15].It was estimated that 20% to 25% of the adult general population and 70% to 80% of T2DM patients had MetS worldwide [16].Individuals with MetS are more likely to have a higher risk of heart attacks and cardiovascular diseases (CVD) compared to those without MetS [4,17].Furthermore, it is documented that the risk of CVD development is greater among individuals who have a combination of T2DM and MetS compared to those who have either condition alone [18].
While the burden of communicable diseases has traditionally been the major focus of public health initiatives in SSA, the rise of noncommunicable diseases like T2DM and MetS is now posing a signifcant threat to the region's health and socioeconomic development.Unlike prior studies [19,20] that explored MetS in broader African populations or specifc country, the current study aimed to systematically review the available evidence and provide an estimate of the pooled prevalence of MetS among SSA individuals with T2DM.Spotlighting MetS within the context of T2DM in SSA ofers a more targeted understanding of MetS within a unique subset of the African population, providing valuable information for healthcare practitioners and researchers focusing on this demographic.

Design and Registration.
We conducted a systematic review and meta-analysis of observational studies, all of which were cross-sectional study designs done across SSA.Tis systematic review and meta-analysis was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guideline [21].Te study protocol was registered in the PROSPERO, an international prospective register of systematic reviews protocols on health-related topics CRD42023455576 [22].1).Te secondary aim was to describe the prevalence of individual components of MetS among T2DM patients, according to the specifc MetS defnition criteria among T2DM individuals in SSA.

Data Source and Search Strategy.
We conducted a comprehensive systematic literature search to identify studies reporting the prevalence of MetS among T2DM patients in the sub-Saharan African population.Te search utilized a combination of Medical Subject Headings (MeSH) and free text words across various electronic databases and search engine, including MEDLINE-PubMed, EMBASE, Scopus, African Index Medicus, African Journal Online, and Google Scholar.Inclusion criteria were limited to English-language studies published from the inception of databases until July 31, 2023.Additionally, a snowball search was performed on the reference lists of all relevant included studies.Te search strategy focused on three key elements: metabolic syndrome, type 2 diabetes mellitus, and sub-Saharan Africa.Tese searches were independently performed by two authors: N. M and H. N. Te detailed search strategy used for the databases is presented in the Supplementary Material S1.To manage references and remove duplicates, we used Rayyan, an online web application.

Inclusion and Exclusion
Criteria.Te inclusion criteria were as follows: all observational studies reporting the prevalence of MetS and its subcomponents among T2DM individuals in sub-Saharan African populations, studies reporting metabolic syndrome using IDF criteria and/or NCEP-ATP III 2004, and publications with full text in English.Te full text of studies meeting these criteria was retrieved and screened for eligibility.Whereas, nonoriginal research articles, such as review articles, editorials, case reports, letters, or commentaries, studies describing MetS in populations other than sub-Saharan Africa, T2DM, and 2 Journal of Obesity those with unclear or unspecifed methods of diagnosing metabolic syndrome were excluded.

Study Selection and Quality
Assessment.Two authors (N.M. and H. N.) independently conducted the literature search and screened the titles, abstracts, and keywords of all the studies retrieved from online database searches for possible inclusion in the review.Furthermore, the relevant articles were obtained in full text, and after a thorough reading of the full-text articles, the included studies were identifed based on the assessment of inclusion and exclusion criteria.Any discrepancies during the entire selection process between the two authors were resolved either through consensus or consultation with the third author (G.J).Te search, screening, and study identifcation process are summarized in Figure 1.Te methodological quality and risk of bias of the included studies was assessed using eight aspects of the Joanna Brigg's Institute (JBI) quality checklist for analytical cross-sectional studies [23,24].Two authors (N.M. and H. N.) independently used the tool to evaluate the inclusion criteria, measurement of exposure and outcome variables, confounding adjustment, and appropriateness of statistical analysis.Studies that scored 50% or higher on the quality assessment were considered to be of good quality.Full details regarding the appraisal checklist are provided in Table 2.

Data Extraction.
Extraction of relevant data from the included studies was independently performed by two authors (N.M and H. N).Information regarding authors, year of publication, geographical location, years of survey, study design, sample size, gender, mean age, sampling techniques, diagnostic criteria for defning metabolic syndrome, and relevant clinic outcomes of interest were collected using a standardized data extraction form.Extracted data were then checked for its accuracy and consistency by a third author (G.J).

Statistical Analysis.
Te extracted data were exported to computer software RStudio version 2023.06.1 + 524 for data synthesis, analysis, and generation of forest and funnel plots.
Evidence of between study variance due to heterogeneity was assessed using Cochran's Q statistic and the I 2 statistic [55,56].Furthermore, in order to explore potential sources of heterogeneity across the included studies, subgroup and sensitivity analyses were performed to comprehensively assess the overall efect size within the included studies.A random-efects model with inverse variance was used to obtain an overall summary estimate of the prevalence across studies.Point estimation with a confdence interval of 95% was used.Te presence of publication bias was examined through the utilization of funnel plots, further enhanced by formal statistical assessment using Egger's test [57].

Study Selection.
As shown in Figure 1, a preliminary search of online databases using a combination of MeSH and free text words retrieved a total of 1418 potential articles, and additional 3 articles were found through manual citation searching.After removing duplicates, 928 articles remained, which were then screened based on their titles and abstracts, resulting in the elimination of further 872 articles that were irrelevant to the research question.Among the 56 articles that underwent full-text review, ultimately 30 articles met the inclusion criteria and were included in this review.

Burden of Metabolic Syndrome Using NCEP-ATP III 2004
and IDF Criteria.Te weighted pooled prevalence of MetS among T2DM individuals in sub-Saharan Africa using studies reported prevalence based on gender, revealing that the pooled prevalence of MetS among females in SSA was signifcantly higher compared to males (73.5% vs. 50.5%).Meanwhile, the results of subgroup analysis based on sample size showed the highest prevalence in studies with ≥250 subjects compared to those with <250 subjects (67.0% vs. 55.2%), as depicted in Supplementary Table 2. Furthermore, subgroup analysis based on IDF criteria, as shown in Supplementary Table 3, revealed a higher pooled prevalence among females (71.6%) compared to males (44.5%) among the 11 studies that reported prevalence based on gender.Among the 12 reports that specifed participant mean age, the pooled prevalence was comparable across the two categories of mean age: <50 years and ≥50 years.Additionally, sensitivity analyses were conducted using the leave-one-out approach to evaluate the infuence of individual studies on the overall estimate of MetS, based on the NCEP-ATP III 2004 and IDF criteria.Te results indicated no substantial evidence for the infuence of any single study on the overall pooled prevalence of MetS among individuals with T2DM in SSA (Figures 5 and 6).To further explore the observed heterogeneity in the study, we conducted a meta-regression to account for this.Te analysis revealed that gender had a signifcant infuence on the overall efect sizes in both NCEP-ATP III 2004 and IDF (p < 0.0001, 0.0007, respectively) and studies with a sample size ≥250; for NCE-P-ATP III 2004, there was a signifcant infuence observed at p value 0.0106.

Publication Bias.
A funnel plot of the pooled prevalence of MetS and Begg's statistical tests at a 5% signifcance level was used to assess the presence of potential publication bias

Study
Random effects model Heterogeneity:

Discussion
Te association between T2DM and MetS has been thoroughly investigated.To our knowledge, this is the frst systematic review and meta-analysis that evaluated the weighted pooled prevalence of MetS in individuals with T2DM in sub-Saharan Africa using specifc diagnostic criteria for metabolic syndrome.Te fndings of this systematic review indicate that the weighted pooled prevalence of MetS was 63.1% (95% CI: 57.9-68.1)and 60.8% (95% CI: 50.7-70.0)using NCEP-ATP III 2004 and IDF criteria, respectively.Te observed disparities in the prevalence of MetS when applying the NCE-P-ATP III 2004 criteria versus the IDF criteria are noteworthy.Te prevalence was slightly higher (63.1%) when the NCEP-ATP III 2004 criteria were used, compared to the IDF criteria (60.8%).Tese diferences can be attributed to variations in the diagnostic components and thresholds employed by each set of criteria [58].Similar fndings regarding the variation in MetS prevalence based on diagnostic criteria have been reported in many studies conducted in diferent parts of the world [59,60].Interestingly, when we compare our fndings with those from other regions and study populations, we observe divergent outcomes.For instance, our fndings are somewhat consistent with results reported in a systematic review among African T2DM patients (66.9%) [19] and Ethiopian T2DM patients (63.78%) [20].However, the current weighted pooled prevalence of MetS using IDF criteria (60.8%) was higher than the prevalence estimated globally, which typically ranges between 20% and 25% when using similar diagnostic criteria [16].Notably, subgroup analysis by gender revealed a considerably higher pooled prevalence of MetS in females, at 73.5% (95% CI: 67.4-79.5),compared to males at 50.5% (95% CI: 43.8-57.2) according to the NCEP-ATP III 2004.Similarly, a higher pooled prevalence was observed according to the IDF criteria among females, reaching 71.6% (95% CI: 60.2-82.9),compared to males at 44.5% (95% CI: 34.2-54.8).Tis fnding aligns with reports from systematic reviews conducted among various populations, including SSA African [61], Ghanaian [62], Bangladesh [63], and mainland China [64].Te possible reason for the higher prevalence in females could be gender-specifc increased MetS risk factors among women, such as menopause, contraceptive therapy use, elevated body weight, and increased waist circumference, in comparison to men [65].Based on IDF criteria, among the included studies, the highest weighted pooled prevalence was observed in Nigeria at 80.2% (95% CI: 47.1-99.9),while Ethiopia had the lowest at 52.0% (95% CI: 48.3-55.8).Tis contrasts with a review by Shiferaw et al. [66] that identifed the highest prevalence of MetS in Ethiopia.However, their study combined studies with varying diagnostic criteria, unlike our report, which might account for this variation.Te diferences in MetS prevalence between Nigeria and Ethiopia found on the current review stem from a blend of varying dietary patterns, lifestyle distinctions, disparities in healthcare infrastructure, and cultural infuences.
Generally, our fndings difer from those of many other studies around the world.In a systematic review conducted among healthy South Asians, a prevalence of MetS was reported as 26.1% (ATP III), 29.8% (IDF), and 32.5% (modifed ATP III) [67].Similarly, a quantitative synthesis of 111 studies conducted among the Indian adult general population reported a prevalence of 29% (NCEP ATP-III) and 34% (IDF) [68].Te observed discrepancies in the prevalence of MetS reported among diferent studies around the world are signifcant.Tese discrepancies might be due to diferences in intrinsic study design, sample size, and characteristics of the study participants, such as comorbidities, geographical locations, urbanization, and lifestyle factors, including physical inactivity and unhealthy eating habits [69,70].Moreover, the current review focused on sub-Saharan African Type 2 Diabetes Mellitus individuals.T2DM appears to play a pivotal role in the pathogenesis and exacerbation of MetS, such that individuals with T2DM are more likely to have MetS, increasing their susceptibility to cardiovascular complications [11,71].
According to the data compiled in this review, the pooled prevalence of MetS components was as follows: central obesity at 55.9% and 61.6%; low HDL-c at 43.3% and 49.9%; hypertriglyceridemia at 48.0% and 49.2%; and hypertension at 54.8% and 56.1%, according to NCEP-ATP III 2004 and IDF criteria, respectively.Central obesity emerged as the most frequent metabolic syndrome component in this systematic review.Visceral adiposity has long been recognized as a central player in insulin resistance and is linked to a heightened risk of type 2 diabetes mellitus and cardiovascular diseases [72].Moreover, high blood pressure and abnormal lipid profles were also found to be prevalent in our review.Tus, our fndings underscore the importance of a holistic approach to patient care, integrating strategies to mitigate MetS components alongside T2DM management to prevent adverse health efects such as CVD [73,74].
Te strengths of the present study include its comprehensive database search using varying combinations of keywords and well-defned inclusion/exclusion criteria.However, we wish to acknowledge several limitations in the current study.Firstly, signifcant heterogeneity was observed across the included studies, and this heterogeneity persisted even after stratifcation for diagnostic criteria.Secondly, the diversity in sub-Saharan African populations, as SSA is home to various ethnic, cultural, and socioeconomic groups, may exhibit diferent risk factors and disease profles.Terefore, the generalizability of fndings across this region may be limited, as the prevalence and associations of MetS in T2DM can vary among these subpopulations.

Conclusion
Although limited in scope, the fndings presented here underscore the alarming prevalence of MetS among individuals with T2DM in sub-Saharan Africa.Tis trend may be directly linked to the rapid economic development and urbanization occurring in the region.Tis swift industrialization can lead to signifcant changes in lifestyle patterns and overnutrition, resulting in overweight and obesity, emphasizing the urgent need for comprehensive, region-specifc prevention and management strategies.Encouraging lifestyle modifcations, including regular exercise and balanced diets, is essential.Moreover, it is crucial to develop routine obesity screening procedures.Implementing early interventions and robust public health initiatives are crucial in mitigating the risks associated with central obesity.
Sub-Saharan Africa faces unique health challenges, including limited healthcare resources and the dual burden of communicable and noncommunicable diseases, which must be taken into account when developing efective interventions.Moving forward, it is imperative to prioritize research eforts that not only elucidate the underlying mechanisms of MetS and T2DM but also explore culturally sensitive and sustainable approaches for prevention and treatment.We hope that this systematic review will serve as a foundation for further studies, ultimately leading to more efective strategies and improved health outcomes for individuals in sub-Saharan Africa who are grappling with the challenges of metabolic syndrome and T2DM.

Figure 1 :
Figure 1: Preferred reporting items for systematic reviews and meta-analyses (PRISMA) fow chart.

Figure 2 :
Figure 2: A map of Africa showing the locations of the included studies (created with https://paintmaps.com).

Figure 7 :
Figure 7: Funnel plot for the publication bias based on NCEP-ATP III 2004 criteria.

Figure 8 :
Figure 8: Funnel plot for the publication bias based on IDF criteria.

Table 1 :
Diagnostic criteria of metabolic syndrome according to NCEP-ATP III 2004 and IDF criteria.

Table 5 .
3.5.Subgroup and Sensitivity Analysis.Subgroup analyses were conducted based on gender, country, sample size, and mean age.According to the NCEP-ATP III 2004, a total of 17

Table 2 :
Methodological quality assessment of included studies using Joanna Brigg's Institute quality appraisal (JBI).

Table 3 :
Characteristics of the included studies that evaluated the prevalence of MetS among T2DM in sub-Saharan population.

Table 4 :
Figure 4: Forest plot illustrating the pooled prevalence of MetS with corresponding 95% CIs in sub-Saharan Africa based on IDF criteria.Pooled prevalence of metabolic syndrome component based on NCEP-ATP III 2004.

Table 5 :
Pooled prevalence of metabolic syndrome component based on IDF criteria.